The effect of high-fidelity simulation on clinical competencies in undergraduate nursing students: a systematic review of randomized controlled trials

The effect of high-fidelity simulation on clinical competencies in undergraduate nursing students: a systematic review of randomized controlled trials | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The effect of high-fidelity simulation on clinical competencies in undergraduate nursing students: a systematic review of randomized controlled trials Ibrahim Ghoul, Abdullah Abdullah, Mahmoud Hodrob, Fateh Awwad, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7234638/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background High-fidelity simulation (HFS) has gained prominence in nursing education as a method to enhance clinical competencies in undergraduate nursing students. This systematic review examines the impact of HFS on various aspects of nursing students' clinical competencies. Methods Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we conducted a comprehensive search for randomized controlled trials (RCTs) published in English between 2013 and 2023. Inclusion and exclusion criteria were applied, leading to the selection of 13 relevant studies. Quality assessment and risk of bias analysis were performed using The Cochrane Collaboration's tool for RCTs. Results The systematic review synthesized findings from the selected studies, revealing the positive impact of HFS on nursing students' clinical competencies. These competencies encompassed knowledge acquisition, clinical performance, self-confidence, self-evaluation, critical thinking, problem-solving skills, and anxiety reduction. While there was variability in outcomes such as self-efficacy and satisfaction, HFS consistently demonstrated its effectiveness in enhancing nursing education. Conclusion In conclusion, HFS emerges as a valuable tool for improving the clinical competencies of undergraduate nursing students. This systematic review highlights the multifaceted benefits of HFS in nursing education, encouraging its integration alongside traditional clinical methods. Recommendations include following evidence-based guidelines and fostering collaboration among educators and institutions to further enhance nursing education through HFS. High-Fidelity Simulation Undergraduate Nursing Students Figures Figure 1 Background High-fidelity simulation (HFS) has emerged as a powerful pedagogical tool in nursing education, offering students a realistic, interactive, and safe environment to develop and refine clinical competencies [ 1 – 3 ] Defined as simulation experiences that provide a high degree of realism and interactivity often using advanced manikins, computer-based scenarios, and immersive clinical environments HFS replicates complex patient care situations that nursing students may encounter in clinical practice [ 1 – 3 ]. Clinical competencies, encompassing a combination of knowledge, technical skills, critical thinking, communication, and decision-making abilities, are essential for ensuring safe and effective nursing care [ 1 , 3 , 4 ]. For undergraduate nursing students, developing these competencies is a core component of their professional training and a key predictor of their readiness for real-world clinical settings [ 1 , 3 , 4 ]. In recent years, the integration of HFS into undergraduate nursing curricula has expanded globally, driven by the need to overcome challenges such as limited clinical placement opportunities, increasing patient acuity, and heightened concerns about patient safety [ 1 , 2 ]. Several individual studies have reported promising outcomes associated with HFS, including enhanced clinical judgment, improved psychomotor skills, and increased student confidence [ 1 , 3 , 5 , 6 ]. Randomized controlled trials (RCTs), considered the gold standard in evaluating educational interventions, have been conducted to assess the impact of HFS on various dimensions of nursing performance [ 3 , 4 , 7 ]. However, the evidence remains mixed, with some studies demonstrating significant improvements in competencies, while others show marginal or no differences when compared to traditional teaching methods [ 2 , 8 ]. Despite the growing body of research, a key issue persists: the lack of consensus regarding the effectiveness of HFS in consistently improving clinical competencies among undergraduate nursing students [ 2 , 8 , 9 ]. While some systematic reviews have explored the broader role of simulation in nursing education, few have specifically focused on high-fidelity modalities within the rigorous framework of RCTs [ 2 , 3 ]. This creates a gap in the evidence synthesis needed to guide educators, curriculum developers, and policymakers in making informed decisions about the integration and optimization of HFS in nursing programs [ 2 , 3 ]. This systematic review addresses the problem of insufficient consolidated evidence on the effectiveness of HFS in enhancing clinical competencies in undergraduate nursing students [ 2 , 3 ]. Without a clear understanding of its impact, nursing programs may underutilize or misapply HFS, missing an opportunity to maximize its educational value or investing in costly technologies without adequate justification [ 2 ]. The significance of this study lies in its potential to clarify the role of HFS as an evidence-based educational strategy [ 1 – 3 ]. By synthesizing findings from RCTs, this review will provide robust, high-quality evidence to inform teaching practices, curriculum design, and policy development [ 3 , 4 , 7 ]. Nursing educators will benefit from a clearer understanding of how and when HFS contributes most effectively to student learning, while students stand to gain from improved educational strategies that better prepare them for clinical practice [ 1 , 3 , 4 ]. Ultimately, the findings may contribute to enhanced patient safety and healthcare quality through the development of more competent and confident future nurses [ 1 – 4 , 10 ]. This study is guided by the PICO framework, which provides a structured approach to formulating the research question and guiding evidence synthesis [ 1 , 3 , 10 ]. The Population (P) consists of undergraduate nursing students undergoing clinical education. The Intervention (I) involves the use of high-fidelity simulation as a teaching strategy integrated into nursing curricula. The Comparison (C) is made with traditional teaching methods, such as lectures or low-fidelity simulations, that do not utilize high-fidelity components. The Outcome (O) focuses on the enhancement of clinical competencies, including skills, critical thinking, and decision-making abilities. Using this PICO framework ensures a systematic and focused evaluation of the existing evidence from randomized controlled trials regarding the impact of high-fidelity simulation on nursing education. The aim of this study is to systematically review and synthesize evidence from randomized controlled trials on the effect of high-fidelity simulation on clinical competencies in undergraduate nursing students. Materials and Methods Design The systematic review was conducted and documented following the guidelines set out by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [ 11 ]. Inclusion criteria Only RCT complete articles published in English within peer-reviewed journals were considered. The studies had to focus on the integration of high-fidelity simulation in nursing education and measure the effect on undergraduate nursing students. The studies had to be published between 2013 and 2023. Exclusion criteria Non-RCT studies, Observational research, quasi-experimental studies, conference abstracts, studies conducted outside the specified time frame, and studies that did not specifically measure the effect on nursing students' clinical competencies were excluded. Literature Search and Selection A comprehensive search was conducted on the databases PubMed, ScienceDirect, CINAHL, and one selected related article. The search was limited to articles published between 2013 and 2023. The search terms used were high-fidelity, Nurse, Nursing, Undergraduate, Baccalaureate, Bachelor, Student, and related terms. The search string in databases is in Table 1 . Table 1 The Search String In Databases Database Search String PubMed ((("high"[All Fields] AND ("fidelities"[All Fields] OR "fidelity"[All Fields])) OR "high-fidelity"[All Fields]) AND ("nurse s"[All Fields] OR "nurses"[MeSH Terms] OR "nurses"[All Fields] OR "nurse"[All Fields] OR "nurses s"[All Fields] OR ("nursing"[MeSH Terms] OR "nursing"[All Fields] OR "nursings"[All Fields] OR "nursing"[MeSH Subheading] OR "nursing s"[All Fields]) OR ("nurse s"[All Fields] OR "nurses"[MeSH Terms] OR "nurses"[All Fields] OR "nurse"[All Fields] OR "nurses s"[All Fields])) AND ("undergraduate"[All Fields] OR "undergraduate s"[All Fields] OR "undergraduated"[All Fields] OR "undergraduates"[All Fields] OR ("baccalaureate"[All Fields] OR "baccalaureates"[All Fields]) OR ("bachelor"[All Fields] OR "bachelor s"[All Fields] OR "bachelors"[All Fields]) OR ("student s"[All Fields] OR "students"[MeSH Terms] OR "students"[All Fields] OR "student"[All Fields] OR "students s"[All Fields]) OR ("student s"[All Fields] OR "students"[MeSH Terms] OR "students"[All Fields] OR "student"[All Fields] OR "students s"[All Fields]))) AND (y_10[Filter]) Science Direct (high-fidelity simulation) AND (nurse OR nursing OR nurses) AND (undergraduate OR student OR students OR baccalaureate OR bachelor) CINAHL (high fidelity OR high-fidelity) AND (nurse OR nursing OR nurses) AND (undergraduate OR student OR students OR baccalaureate OR bachelor) The review process was collaboratively conducted by a multidisciplinary team of authors, each contributing to distinct phases to ensure methodological rigor and transparency. On December 5, 2023, the initial electronic search across databases was conducted by Ibrahim Ghoul, who also removed duplicate records using EndNote. Title screening was performed by Abdullah Abdullah and Shurouq Qadous, followed by abstract screening by Mahmoud Hodrob and Fateh Awwad. Full-text assessment for eligibility and detailed data extraction were carried out by Nedal Jaber, Ahmad Hodrob, Buthaina Nazzal, and Malakeh Z. Malak, focusing on methodological quality and relevance. Additional support in quality appraisal and data verification was provided by Nizar Said, Amer Asia, and Wafaa Qaysi. Discrepancies and conflicts during the screening or data extraction stages were resolved through consensus under the leadership of Mohammed Hayek. The initial search strategy yielded 2,791 records. After removing duplicates, 2,334 unique articles remained. Title screening excluded 1,548 records, and abstract screening led to the removal of 764 more. After full-text assessment, 13 randomized controlled trials (RCTs) met the inclusion criteria and were included in this systematic review. The complete study selection process is illustrated in the PRISMA flow diagram (Fig. 1 ). Data Extraction The data extraction process for this systematic review encompassed studies published between January 2013 and 5 December 2023, totaling 13 research articles. These studies uniformly focused on the integration of high-fidelity simulation within nursing education programs, with a specific emphasis on evaluating its effect on the clinical competencies of nursing students. Comprehensive details regarding trial attributes, participant demographics, interventions, control group descriptions, outcome measures related to clinical competency, and concluding remarks can be found in Table 2 , where each study is listed by (Author, year), country, participant characteristics, intervention group, control group, outcome measures pertaining to clinical competency, and key conclusions. In the following section, we provide a synthesized overview of the study characteristics and findings, aligning with the established PICO (Population, Intervention, Comparison, Outcome) framework for systematic reviews. Quality assessment and risk of bias The risk of bias in individual studies included in this systematic review was assessed using The Cochrane Collaboration's tool for assessing the risk of bias specific to randomized controlled trials (RCTs) [ 12 ]. This tool comprehensively evaluates several key domains of potential bias (low risk, high risk, or unclear risk), ensuring the quality and validity of the RCTs in question. Each study was scrutinized for selection bias, with attention to random sequence generation and allocation concealment. Performance bias and detection bias were assessed by examining methods for blinding participants and outcome assessors. Attrition bias was evaluated by examining the handling of incomplete outcome data while reporting bias was examined by assessing whether all predefined outcomes were reported. Moreover, other sources of bias, such as baseline imbalances and funding sources, were considered in the risk of bias assessment. By rigorously applying The Cochrane Collaboration's tool, the systematic review aimed to provide a comprehensive and critical evaluation of each RCT's methodological quality and potential sources of bias. Table 3 represents the Methodological Quality of Included Studies. Table 2 Summary of Included Randomized Controlled Trial (Author, year) / Country Participants Characteristics Experimental Group Control Group Outcome Measures Conclusion (Cengiz et al., 2023) / Turkey [ 13 ] Number: 112 Level: first-year Intervention: post-operative care M/F: 31/81 Number:57 Age:19.63 ± 1.19 Intervention: Scenario-based HFS Number:55 Age: 19.47 ± 1.08 Intervention: in-class learning sessions Problem-solving Self-efficacy HFS outperforms in-class learning for problem-solving and self-efficacy. (Ozdemir & Kaya, 2023) / Turkey [ 14 ] Number: 80 Level: first-year Intervention: Foley catheterization M/F: 7/73 Number: 40 Age: 18.93 ± 1.05 Intervention: Scenario-based + HFS Number: 40 Age: 19.45 ± 1.92 Intervention: low fidelity simulation (LFS) Knowledge performance Satisfaction Self-confidence HFS improved novice nursing students' knowledge, performance, satisfaction, and self-confidence more than LFS (Hodrob et al., 2022) / Palestine [ 15 ] Number: 154 Level: second-year Intervention: airway management M/F: 80/74 Age: 22.2 years Number: 77 Intervention: HFS Number: 77 Intervention: lecture based performance satisfaction self-confidence HFS proved effective in enhancing nursing students' airway management performance, boosting their satisfaction and self-confidence. (Guerrero et al., 2021) / Saudi Arabia [ 16 ] Number: 30 Level: 1st to 4th Age: 24–26 years Number: 15 Intervention: HFS and hands-on training. Number: 15 Intervention: hands-on training performance HFS improves clinical performance. (Haddeland et al., 2021) / Norway [ 17 ] Number: 158 Intervention: blood loss after surgery M/F: 19/139 Age: 21–22 Number: 89 Intervention: HFS Number: 69 Intervention: lecture-based Knowledge self-confidence High-fidelity simulation improves knowledge and self-confidence (Doğru & Aydın, 2020) / Turkey [ 18 ] Number:72 Level: first-year mean age: 19.95 ± 1.77 Intervention: cardiac auscultation Number: 36 Intervention: HFS Number: 36 Intervention: Static manikin Knowledge performance Anxiety Using HFS outperformed traditional methods, improving students' knowledge and performance in cardiac auscultation while reducing anxiety. (Terzi et al., 2019) / Turkey [ 19 ] Number:59 Level: first-year Intervention: blood pressure measurement nursing students Number: 32 Intervention: HFS Number: 27 Intervention: students practice on their peers Self-confidence self-efficacy Anxiety The HFS boosted students' self-confidence and self-efficacy but didn't impact their anxiety levels compared with practice on their peers (Mutlu et al., 2019) / Turkey [ 20 ] Number: 71 Level: 3rd and 4th -year Intervention: heart and lung sounds M/F: 0/71 Number: 36 Intervention: HFS Mean age: 21.53 ± 0.70 Number: 35 Intervention: LFS Mean age: 21.74 ± 1.12 performance HFS more effective in heart and lung sounds performance. (Boostel et al., 2017) / Brazil [ 21 ] Number: 52 Intervention: cardiothoracic physical examination Number: 27 Mean age: 20.32 ± 1.79 Intervention: Theoretical /clinical class + HFS Number: 25 Mean age: 21.11 ± 2.47 Intervention: Theoretical /clinical class Critical thinking Self-evaluation Simulation influences perception of pressures, encourages critical thinking and Self-evaluation. (Labant & Palmer, 2017) / USA [ 22 ] Number: 26 Level: junior-level Course: Maternal Neonate Clinical Number: 14 Intervention: lecture/video and hands-on training using a HFS Number: 12 Intervention: lecture/video Knowledge HFS group had lower discrepancy scores, closer to expert level and improve knoledge. (Baptista et al., 2016) / Portugal [ 23 ] Number: 85 Level: 4th -year Intervention: Critical condition M/F: 6/79 Mean age: 21.89 years (SD = 2.81 years). Number: 49 Intervention: HFS Number: 36 Intervention: Medium-fidelity simulation Satisfaction HFS investment advantageous for student Satisfaction. (Aqel & Ahmad, 2014) / Jordan [ 24 ] Number: 90 M/F: 19/71 Intervention: CPR Number: 45 Intervention: HFS Number: 45 Intervention: LFS Knowledge performance HFS excelled in knowledge and performance. Both experienced skill decline after three months. (White et al., 2013) / USA [ 25 ] Number: 54 Level: senior-level Intervention: Distributive Shock M/F: 7/47 Number: 16 Intervention: HFS Number: 38 Intervention: lecture-based Knowledge Self-confidence The utilization of HFS did not lead to notable improvements in either Knowledge or Self-confidence. Table 3 Methodological Quality of Included Studies Author (year) Random (selection bias) Allocation (selection bias) performance bias Detection bias attrition bias reporting bias Other Bias (Cengiz et al., 2023) [ 13 ] Low risk Unclear risk Unclear risk High risk Low risk Low risk Low risk (Ozdemir & Kaya, 2023) [ 14 ] low risk high risk high risk high risk low risk High risk high risk (Hodrob et al., 2022) [ 15 ] low risk Unclear risk Unclear risk Unclear risk low risk low risk low risk (Guerrero et al., 2021) [ 16 ] Low risk Low risk Low risk Low risk Low risk low risk low risk (Haddeland et al., 2021) [ 17 ] Low risk Low risk low risk Low risk Low risk low risk low risk (Doğru & Aydın, 2020) [ 18 ] Low risk high risk high risk high risk unclear risk High risk Unclear risk (Terzi et al., 2019) [ 19 ] low risk high risk high risk high risk low risk High risk high risk (Mutlu et al., 2019) [ 20 ] low risk High risk unclear risk high risk low risk High risk Unclear risk (Boostel et al., 2017) [ 21 ] Low risk High risk High risk High risk Low risk Low risk Low risk (Labant & Palmer, 2017) [ 22 ] Low risk Unclear risk Unclear risk Unclear risk Low risk low risk low risk (Baptista et al., 2016) [ 23 ] Low risk High risk High risk High risk Low risk Low risk Low risk (Aqel & Ahmad, 2014) [ 24 ] Low risk Unclear risk High risk High risk Low risk Low risk Low risk (White et al., 2013) [ 25 ] low risk High risk unclear risk low risk unclear risk High risk high risk Result Participants and interventions : The research presented in this section encompasses thirteen distinct studies, collectively involving 1,320 participants, and explores various facets of healthcare education across different regions and interventions. These studies shed light on the diversity of approaches and methodologies employed in healthcare education research, reflecting the global nature of this field. Table 3 presents the methodological quality assessment of 13 included randomized controlled trials, highlighting varying levels of bias across different domains. Random sequence generation (selection bias) was rated as low risk in all studies, suggesting appropriate randomization methods. However, allocation concealment showed more variability, with several studies such as Ozdemir & Kaya (2023) [ 14 ], Doğru & Aydın (2020) [ 18 ], and others rated as high risk, indicating potential bias in group assignment. Performance and detection bias were frequently rated as high or unclear, especially in studies involving educational interventions where blinding was challenging. Attrition bias was mostly low across studies, suggesting acceptable handling of dropouts. While reporting bias was generally low, a few studies like Ozdemir & Kaya (2023) [ 14 ] and Terzi et al. (2019) [ 19 ] had high risk, indicating selective outcome reporting. Other bias was often rated as low, though some studies presented unclear or high risk. Overall, while most studies demonstrated adequate randomization, concerns remain about blinding and allocation concealment, potentially impacting internal validity. In our examination of the control groups within these studies, we observe a wide range of interventions and participant characteristics. These variations underscore the need for flexibility in healthcare education research to cater to the specific needs and contexts of different regions and institutions. For instance, Cengiz et al. and Ozdemir & Kaya in Turkey employed traditional in-class learning and "LFS," respectively, as control interventions, emphasizing the importance of comparing innovative educational methods with established ones [ 13 , 14 ]. Hodrob et al. in Palestine and Haddeland et al. in Norway utilized lecture-based teaching in their control groups, emphasizing the global prevalence of this traditional approach [ 15 , 17 ]. In contrast, Doğru & Aydın in Turkey, Terzi et al., and Mutlu et al. exclusively employed static manikins, reflecting the range of simulation tools available for healthcare education [ 18 – 20 ]. Boostel et al. in Brazil and Labant & Palmer in the USA integrated theoretical and clinical class-based education in their control groups, highlighting the importance of theoretical foundations in healthcare education [ 21 , 22 ]. Baptista et al. in Portugal introduced medium-fidelity simulation for their control group, showcasing the diverse spectrum of simulation technologies [ 23 ]. Finally, Aqel & Ahmad in Jordan and White et al. in the USA used "LFS" and lecture-based instruction, respectively, as control interventions, indicating that traditional methods persist alongside innovative approaches [ 24 , 25 ] ( Table 2 ). Turning our attention to the experimental groups, we find an equally diverse set of interventions and participant characteristics. The variety of educational approaches reflects the dynamic nature of healthcare education research. For example, Cengiz et al. and Ozdemir & Kaya in Turkey incorporated scenario-based High-Fidelity Simulation (HFS) in their experimental groups, underscoring the growing importance of immersive simulation experiences [ 13 , 14 ]. Hodrob et al. in Palestine and Haddeland et al. in Norway exclusively employed HFS, emphasizing its effectiveness in teaching critical healthcare skills [ 15 , 17 ]. Guerrero et al. (2021) in Saudi Arabia combined HFS with hands-on training, showcasing the potential benefits of multifaceted approaches. Similarly, Doğru & Aydın, Terzi et al., and Mutlu et al. in Turkey embraced HFS as the primary mode of intervention, aligning with the trend toward high-fidelity simulations [ 18 – 20 ]. Boostel et al. in Brazil integrated theoretical/clinical classes with HFS, reflecting a comprehensive approach to healthcare education [ 21 ]. Labant & Palmer in the USA combined lecture, video, and hands-on training, demonstrating the importance of multimodal education [ 22 ]. Baptista et al. in Portugal focused exclusively on HFS for their experimental group, indicating the significance of this simulation method [ 23 ]. Finally, Aqel & Ahmad in Jordan and White et al. in the USA employed HFS as the primary mode of intervention in their experimental groups, further highlighting its prominence [ 24 , 25 ]. Outcome measures : Knowledge Six articles revealed that the high-fidelity simulation enhanced the knowledge among undergraduate nursing students. A recently conducted study in Turkey by Ozdemir and Kaya, found the knowledge among the students who had the opportunity of training through HFS and Scenario-based learning on foly catheterization was higher than the students of Low-Fidelity Simulation [ 14 ]. Another conducted study by Doğru and Aydın, In Turkey, found that the HFS in comparison to traditional teaching methods improved significantly the level of knowledge in cardiac auscultation [ 18 ]. Haddeland et al., conducted a study among Norway undergraduate nursing students and found that HFS improved knowledge about blood loss after surgery in comparison to the control group who received lecture-based education [ 17 ]. Labant and Palmer, found the effect of HFS in addition to the hands-on training on knowledge among undergraduate students who underwent a Maternal and Neonatal clinical course is better than the students who received training via lectures and videos [ 22 ]. These are similar to another two studies in which the level of knowledge where targeted and improved, the HFS training where about CPR versus LFS for the first study and the other was about Distributive Shock for the group of HFS and lecture-based education [ 15 , 24 ]. Performance six studies from various locations demonstrated a significant improvement in clinical performance skills through high-fidelity simulation. Ozdemir and Kaya (2023)in Turkey compared high-fidelity simulation for Foley catheterization skills with routine teaching methods, concluding that high-fidelity simulation significantly enhanced clinical performance skills in this context. Guerrero et al. in Saudi Arabia investigated the impact of simultaneous high-fidelity simulation and hands-on clinical training on clinical performance skills among 120 nursing interns, with results indicating an improvement [ 16 ]. Labant and Palmer in the USA studied 26 junior-level nursing students and found that high-fidelity simulation manikin training effectively improved clinical performance skills, bringing participants closer to expert-level performance [ 22 ]. Mutlu et al. in Turkey compared high-fidelity and low-fidelity simulators for heart and lung sound recognition among 71 third-year female nursing students, concluding that high-fidelity simulation was more effective in this aspect [ 20 ]. Aqel and Ahmad compared the HFS effects on the performance of undergraduate students versus Low Fidelity Simulation on Cardiopulmonary Resuscitation and found that the HFS is better than the LFS group in conducting CPR [ 24 ]. Furthermore, Doğru and Aydın, in Turkey examined the effectiveness of simulation for administering intra-muscular injections among 72 first-year nursing students, concluding that simulation was effective in enhancing clinical performance skills [ 18 ]. Hodrob et al. found that HFS for teaching students airway management is better than the lecture-based methodology among undergraduate nursing students [ 15 ]. Self-Confidence. Self-confidence in nursing education emerges as a complex and nuanced theme when examining the findings of the five pertinent articles. Ozdemir & Kaya's study conducted in Turkey underscored that High-Fidelity Simulation (HFS) contributed significantly to enhancing self-confidence among novice nursing students [ 14 ]. Similarly, Hodrob et al.'s research in Palestine observed a notable boost in self-confidence following HFS interventions focused on airway management performance [ 15 ]. Terzi et al. and Haddeland et al. yielded results aligned with these findings, showing an improvement in students' self-confidence [ 17 , 19 ]. Conversely, White et al. in the USA did not report substantial improvements in self-confidence through HFS [ 25 ]. Satisfaction Satisfaction with the educational approach was explored in 3 studies. Ozdemir & Kaya (2023) and Hodrob et al. found that HFS improved student satisfaction [ 15 ]. Baptista et al. in Portugal also emphasized the advantageous nature of HFS investment for student satisfaction [ 23 ]. Self-Efficacy Self-efficacy was another critical competency assessed in these studies. Two studies out of 13 studies examined Self-Efficacy among the groups, Cengiz et al. in Turkey found that high-fidelity simulation improved self-efficacy among first-year nursing students [ 13 ]. Another study found that self-efficacy improved among the HFS more than the group who practiced on their peers in terms of blood pressure measurement [ 19 ]. Anxiety Two studies addressed the issue of anxiety. Doğru & Aydın reported that HFS reduced anxiety levels, suggesting that it can create a more comfortable learning environment [ 18 ]. However, Terzi et al. did not find significant differences in anxiety levels compared to peer practice, indicating that the impact of HFS on anxiety may vary [ 19 ]. Problem-Solving Only one study out of the 13 studies included in this systematic review found that the HFS had a higher influence in promoting problem-solving skills among undergraduate nursing students compared to the in-class learning sessions. Cengiz et al. conducted a study among the first year of undergraduate nursing students to examine the problem-solving skills related to post-operative care and found the HFS group had better skills compared to the in-class learning sessions group [ 13 ]. Self-Evaluation Examining the findings of Boostel et al.'s study conducted in Brazil [ 21 ], self-evaluation emerges as a crucial dimension of nursing education impacted by HFS. The research underscores that HFS encourages nursing students to engage in rigorous self-assessment and reflection on their performance and decision-making processes within simulated clinical scenarios. By actively participating in the simulation experience and evaluating their actions, students can identify areas for improvement and refine their clinical competencies. Boostel et al.'s findings emphasize the role of HFS in fostering a culture of self-awareness and self-improvement among nursing students, ultimately contributing to their growth as reflective and accountable healthcare professionals [ 21 ]. This highlights the significance of incorporating HFS as an effective tool for enhancing self-evaluation skills within nursing education programs Critical thinking Drawing insights from Guerrero et al.'s research in Saudi Arabia, critical thinking emerges as a pivotal aspect of nursing education [ 16 ]. The study underscores the significant role that HFS plays in influencing critical thinking skills among nursing students. This research highlights that HFS interventions contribute to fostering the ability of students to analyze complex clinical scenarios, question assumptions, and make informed decisions. As demonstrated in the study, HFS provides a conducive environment for students to practice critical thinking within the context of real-life clinical situations, enhancing their capacity to address challenges in healthcare effectively. Consequently, this emphasizes the vital importance of integrating HFS into nursing curricula to cultivate the critical thinking skills essential for future nursing professionals. Discussion The study showed that the high-fidelity simulation positively impacted knowledge. A recent study showed that clinical competency improved in performing the Foley catheterization, in addition to improvement their knowledge [ 14 ]. This is similar to the result of other published studies [ 15 , 17 , 18 , 22 , 24 ]. On the other hand, multiple studies showed the positive influence of HFS on undergraduate nursing student's performance [ 14 – 16 , 18 , 20 , 22 , 24 ]. This reveals the potential of high-fidelity simulation as a good tool in education and training, which leads to nurses graduating with better theoretical and clinical skills, and this can be interpreted in more patient safety and improved nursing confidence. The study revealed another finding, including a positive enhancement of student’s critical thinking skills, problem-solving skills, and decision-making skills. According to Cengiz et al., the high-fidelity simulation positively impacted the students’ skills in problem-solving [ 13 ]. Critical thinking also impacted positively [ 16 ]. This implies that the immersive and realistic quality of high-fidelity simulation scenarios can help students gain more management and leadership skills. The studies revealed another positive outcome for high-fidelity simulation among undergraduate nurses, such as improved student self-confidence and self-efficacy. Terzi et al. found that the self-confidence among the students enhanced related to high fidelity simulation [ 19 ]. These results are similar to the results of other studies [ 14 , 15 ]. These results in contrast to one study result [ 25 ]. Self-efficacy showed improvement among the students of high-fidelity simulation as reported by Cengiz et al [ 13 ]. The systematic review results showed another positive outcome for the high-fidelity simulation. Hodrob et al. and Ozdemir & Kaya [ 14 , 15 ], reported that satisfaction was improved among the students due to high-fidelity simulation. While the level of anxiety was impacted positively due to HFS Doğru & Aydın, and Terzi et al. [ 18 , 19 ] Also, the self-evaluation among the students was encouraged and enhanced [ 21 ]. This implies that the immersive and realistic quality of high-fidelity simulation scenarios can help students confidently approach clinical issues, which is essential in the healthcare industry. These findings show the overall benefits of high-fidelity simulation in nursing education. It not only improves clinical capabilities, but it also improves students' general contentment, mental health, and critical thinking ability. This all-encompassing approach to nursing education can result in balanced, confident, and competent nursing practitioners who are better prepared to fulfill the needs of the healthcare industry. High-fidelity simulation is a valuable tool for enhancing the clinical competencies of undergraduate nursing students. However, its effectiveness is influenced by various factors, such as the simulation scenario, the debriefing process, and the instructor's role. Therefore, we suggest that nursing educators use high-fidelity simulation as a complementary method to traditional clinical education, rather than a replacement. We also recommend that nursing educators follow evidence-based guidelines and best practices for designing, implementing, and evaluating high-fidelity simulation. Furthermore, we encourage nursing educators to collaborate with other disciplines and institutions to share their experiences and resources for high-fidelity simulation. In addition to these recommendations. Future research in this area should aim to address the identified limitations and provide a more comprehensive understanding of the role of high-fidelity simulation in nursing education. Additionally, ongoing evaluation of the evolving technology and educational practices is crucial to ensure the continued relevance and effectiveness of high-fidelity simulation in preparing nursing students for clinical practice. This study was limited to undergraduate nursing students in English-language studies published between 2013 and 2023. Thus, the findings may not be generalizable to other populations or periods. Conclusion In conclusion, the comprehensive review of thirteen diverse studies in healthcare education reveals a multifaceted landscape of interventions, outcomes, and participant characteristics. These studies collectively involve 1,320 participants and span various regions, shedding light on the global nature of healthcare education research. In examining the control and experimental groups, it becomes evident that the interventions employed vary widely, reflecting the flexibility required to cater to the unique needs and contexts of different regions and institutions. Traditional methods, lecture-based teaching, hands-on training, and a range of simulation technologies all find a place within the spectrum of interventions. Notably, High-Fidelity Simulation (HFS) emerges as a prominent educational tool, positively impacting knowledge acquisition, clinical performance, self-confidence, and self-evaluation. While HFS consistently demonstrates its effectiveness, other dimensions such as self-efficacy, satisfaction, and anxiety exhibit varying results across studies. Critical thinking and problem-solving skills also gain importance as outcomes are influenced by HFS, as demonstrated in the relevant research. These findings underscore the dynamic and adaptive nature of healthcare education, emphasizing the need for educators and institutions to continually evaluate and integrate innovative approaches like HFS to ensure the best possible education for future healthcare professionals. Declarations Ethics approval and consent to participate This systematic review did not involve human subjects directly; therefore, ethical approval was not sought. The review exclusively focused on the analysis of previously published research articles and did not require primary data collection from individuals or the involvement of ethical review boards. Clinical trial registration Clinical trial number: not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Author Contribution The initial electronic search across databases was conducted by Ibrahim Ghoul, who also removed duplicate records using EndNote. Title screening was performed by Abdullah Abdullah and Shurouq Qadous, followed by abstract screening by Mahmoud Hodrob and Fateh Awwad. Full-text assessment for eligibility and detailed data extraction were carried out by Nedal Jaber, Ahmad Hodrob, Buthaina Nazzal, and Malakeh Z. Malak, focusing on methodological quality and relevance. Additional support in quality appraisal and data verification was provided by Nizar Said, Amer Asia, and Wafaa Qaysi. Discrepancies and conflicts during the screening or data extraction stages were resolved through consensus under the leadership of Mohammed Hayek. Acknowledgement The authors would like to thank An-Najah National University (www.najah.edu) for the technical support provided to publish the present manuscript Data Availability The data that support the findings of this study are available from the corresponding author upon a reasonable request. References Lei Y, Zhu L, Sa Y, Cui X-S. Effects of high-fidelity simulation teaching on nursing students' knowledge, professional skills and clinical ability: A meta-analysis and systematic review. Nurse Educ Pract. 2022;60:103306. Hanshaw S, Dickerson S. High fidelity simulation evaluation studies in nursing education: A review of the literature. Nurse Educ Pract. 2020;46:102818. Alshehri F, Jones S, Harrison D. The effectiveness of high-fidelity simulation on undergraduate nursing students' clinical reasoning-related skills: A systematic review. Nurse Educ Today. 2022;121:105679. Fung J, Chan SL, Chan CK, Lam CF, Chau YS, Lam WH, Cheng CCW, Lai MH. Enhancing nursing students' clinical competency using a multi-patient simulation learning model: A randomized controlled study. Nurse Educ Today. 2024;140:106292. Ayed A, Malak M, Alamer R, Batran A, Salameh B, Fashafsheh I. Effect of high fidelity simulation on clinical decision-making among nursing students. Interact Learn Environ. 2021;31:2185–93. Ayed A, Khalaf I, Fashafsheh I, Saleh A, Bawadi H, Abuidhail J, Thultheen I, Joudallah H. Effect of High-Fidelity Simulation on Clinical Judgment Among Nursing Students. Inquiry: J Med Care Organ Provis Financing 2022, 59. Chabrera C, Curell L, Rodríguez-Higueras E. Effectiveness of high versus mixed-level fidelity simulation on undergraduate nursing students: A randomised controlled trial. Nurse Educ Pract. 2024;82:104206. Blum C, Borglund S, Parcells D. High-Fidelity Nursing Simulation: Impact on Student Self-Confidence and Clinical Competence. Int J Nurs Educ Scholarsh 2010, 7. O'Rourke L, Morrison M, Grimsley A, Cotter V. High-fidelity simulation and nurse clinical competence-An integrative review. J Clin Nurs 2021. 王 X晓W, 杨 Y, 胡 S莎H. Teaching nursing students: As an umbrella review of the effectiveness of using high-fidelity simulation. Nurse Educ Pract. 2024;77:103969. Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M, Shekelle P, Stewart LA. Group P-P: Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst reviews. 2015;4:1–9. Higgins JP, Altman DG, Gøtzsche PC, Jüni P, Moher D, Oxman AD, Savović J, Schulz KF, Weeks L, Sterne JA. The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. bmj 2011, 343. Cengiz Z, Gürdap Z, Oltuluoğlu H, Aslan H, Aktura SÇ. Developing nursing students' self-efficacy and problem solving skills via high-fidelity simulation. Teach Learn Nurs. 2023;18(4):e167–73. Ozdemir NG, Kaya H. The effectiveness of high-fidelity simulation methods to gain Foley catheterization knowledge, skills, satisfaction and self-confidence among novice nursing students: A randomized controlled trial. Nurse Educ Today. 2023;130:105952. Hodrob AMS, Malak MZ, Ayed A. Effect of high-fidelity simulation airway management training program on nursing students’ performance, satisfaction, and self-confidence in Palestine. Interact Learn Environ. 2024;32(1):325–39. Guerrero JG, Hafiz AH, Eltohamy NAE, Gomma N, Al Jarrah I. Repeated exposure to high-fidelity simulation and nursing interns’ clinical performance: impact on practice readiness. Clin Simul Nurs. 2021;60:18–24. Haddeland K, Slettebø Å, Svensson E, Tosterud RB, Wangensteen S, Fossum M. The effects of using high-fidelity simulation in undergraduate nursing education: A multicenter randomized controlled trial with a process evaluation. Int J Educational Res. 2021;109:101813. Doğru BV, Aydın LZ. The effects of training with simulation on knowledge, skill and anxiety levels of the nursing students in terms of cardiac auscultation: A randomized controlled study. Nurse Educ Today. 2020;84:104216. Terzi B, Topbaş E, Bingöl G, Aydoğdu SGM. Comparison of the effects of two different teaching methods in blood pressure measurement training: a randomized controlled study. Blood Press Monit. 2019;24(6):294–8. Mutlu B, Yılmaz OE, Dur S. The effect of high-and low-fidelity simulators in learning heart and lung sounds by undergraduate nurses: a randomized controlled trial. Contemp Nurse. 2019;55(4–5):351–9. Boostel R, Felix JVC, Bortolato-Major C, Pedrolo E, Vayego SA. Mantovani MdF: Tensión del estudiante de enfermería en la simulación clínica: ensayo clínico aleatorizado. Revista Brasileira de Enfermagem. 2018;71:967–74. Labant AL, Palmer EA. Teaching neonatal abstinence syndrome using simulation. Clin Simul Nurs. 2017;13(6):254–7. Baptista RC, Paiva LA, Goncalves RF, Oliveira LM, Pereira MFC, Martins JC. Satisfaction and gains perceived by nursing students with medium and high-fidelity simulation: A randomized controlled trial. Nurse Educ Today. 2016;46:127–32. Aqel AA, Ahmad MM. High-fidelity simulation effects on CPR knowledge, skills, acquisition, and retention in nursing students. Worldviews Evidence‐Based Nurs. 2014;11(6):394–400. White A, Brannan J, Long J, Kruszka K. Comparison of instructional methods: Cognitive skills and confidence levels. Clin Simul Nurs. 2013;9(10):e417–23. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Clinical competencies, encompassing a combination of knowledge, technical skills, critical thinking, communication, and decision-making abilities, are essential for ensuring safe and effective nursing care [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. For undergraduate nursing students, developing these competencies is a core component of their professional training and a key predictor of their readiness for real-world clinical settings [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn recent years, the integration of HFS into undergraduate nursing curricula has expanded globally, driven by the need to overcome challenges such as limited clinical placement opportunities, increasing patient acuity, and heightened concerns about patient safety [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Several individual studies have reported promising outcomes associated with HFS, including enhanced clinical judgment, improved psychomotor skills, and increased student confidence [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Randomized controlled trials (RCTs), considered the gold standard in evaluating educational interventions, have been conducted to assess the impact of HFS on various dimensions of nursing performance [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. However, the evidence remains mixed, with some studies demonstrating significant improvements in competencies, while others show marginal or no differences when compared to traditional teaching methods [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDespite the growing body of research, a key issue persists: the lack of consensus regarding the effectiveness of HFS in consistently improving clinical competencies among undergraduate nursing students [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. While some systematic reviews have explored the broader role of simulation in nursing education, few have specifically focused on high-fidelity modalities within the rigorous framework of RCTs [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This creates a gap in the evidence synthesis needed to guide educators, curriculum developers, and policymakers in making informed decisions about the integration and optimization of HFS in nursing programs [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis systematic review addresses the problem of insufficient consolidated evidence on the effectiveness of HFS in enhancing clinical competencies in undergraduate nursing students [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Without a clear understanding of its impact, nursing programs may underutilize or misapply HFS, missing an opportunity to maximize its educational value or investing in costly technologies without adequate justification [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe significance of this study lies in its potential to clarify the role of HFS as an evidence-based educational strategy [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. By synthesizing findings from RCTs, this review will provide robust, high-quality evidence to inform teaching practices, curriculum design, and policy development [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Nursing educators will benefit from a clearer understanding of how and when HFS contributes most effectively to student learning, while students stand to gain from improved educational strategies that better prepare them for clinical practice [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Ultimately, the findings may contribute to enhanced patient safety and healthcare quality through the development of more competent and confident future nurses [\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study is guided by the PICO framework, which provides a structured approach to formulating the research question and guiding evidence synthesis [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The Population (P) consists of undergraduate nursing students undergoing clinical education. The Intervention (I) involves the use of high-fidelity simulation as a teaching strategy integrated into nursing curricula. The Comparison (C) is made with traditional teaching methods, such as lectures or low-fidelity simulations, that do not utilize high-fidelity components. The Outcome (O) focuses on the enhancement of clinical competencies, including skills, critical thinking, and decision-making abilities. Using this PICO framework ensures a systematic and focused evaluation of the existing evidence from randomized controlled trials regarding the impact of high-fidelity simulation on nursing education.\u003c/p\u003e\u003cp\u003eThe aim of this study is to systematically review and synthesize evidence from randomized controlled trials on the effect of high-fidelity simulation on clinical competencies in undergraduate nursing students.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cb\u003eDesign\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe systematic review was conducted and documented following the guidelines set out by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eInclusion criteria\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOnly RCT complete articles published in English within peer-reviewed journals were considered. The studies had to focus on the integration of high-fidelity simulation in nursing education and measure the effect on undergraduate nursing students. The studies had to be published between 2013 and 2023.\u003c/p\u003e\u003cp\u003e\u003cb\u003eExclusion criteria\u003c/b\u003e\u003c/p\u003e\u003cp\u003eNon-RCT studies, Observational research, quasi-experimental studies, conference abstracts, studies conducted outside the specified time frame, and studies that did not specifically measure the effect on nursing students' clinical competencies were excluded.\u003c/p\u003e\u003cp\u003e\u003cb\u003eLiterature Search and Selection\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA comprehensive search was conducted on the databases PubMed, ScienceDirect, CINAHL, and one selected related article. The search was limited to articles published between 2013 and 2023. The search terms used were high-fidelity, Nurse, Nursing, Undergraduate, Baccalaureate, Bachelor, Student, and related terms. The search string in databases is in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe Search String In Databases\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDatabase\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSearch String\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePubMed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(((\"high\"[All Fields] AND (\"fidelities\"[All Fields] OR \"fidelity\"[All Fields])) OR \"high-fidelity\"[All Fields]) AND (\"nurse s\"[All Fields] OR \"nurses\"[MeSH Terms] OR \"nurses\"[All Fields] OR \"nurse\"[All Fields] OR \"nurses s\"[All Fields] OR (\"nursing\"[MeSH Terms] OR \"nursing\"[All Fields] OR \"nursings\"[All Fields] OR \"nursing\"[MeSH Subheading] OR \"nursing s\"[All Fields]) OR (\"nurse s\"[All Fields] OR \"nurses\"[MeSH Terms] OR \"nurses\"[All Fields] OR \"nurse\"[All Fields] OR \"nurses s\"[All Fields])) AND (\"undergraduate\"[All Fields] OR \"undergraduate s\"[All Fields] OR \"undergraduated\"[All Fields] OR \"undergraduates\"[All Fields] OR (\"baccalaureate\"[All Fields] OR \"baccalaureates\"[All Fields]) OR (\"bachelor\"[All Fields] OR \"bachelor s\"[All Fields] OR \"bachelors\"[All Fields]) OR (\"student s\"[All Fields] OR \"students\"[MeSH Terms] OR \"students\"[All Fields] OR \"student\"[All Fields] OR \"students s\"[All Fields]) OR (\"student s\"[All Fields] OR \"students\"[MeSH Terms] OR \"students\"[All Fields] OR \"student\"[All Fields] OR \"students s\"[All Fields]))) AND (y_10[Filter])\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eScience\u003c/p\u003e\u003cp\u003eDirect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(high-fidelity simulation) AND (nurse OR nursing OR nurses) AND (undergraduate OR student OR students OR baccalaureate OR bachelor)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCINAHL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(high fidelity OR high-fidelity) AND (nurse OR nursing OR nurses) AND (undergraduate OR student OR students OR baccalaureate OR bachelor)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e The review process was collaboratively conducted by a multidisciplinary team of authors, each contributing to distinct phases to ensure methodological rigor and transparency. On December 5, 2023, the initial electronic search across databases was conducted by Ibrahim Ghoul, who also removed duplicate records using EndNote. Title screening was performed by Abdullah Abdullah and Shurouq Qadous, followed by abstract screening by Mahmoud Hodrob and Fateh Awwad. Full-text assessment for eligibility and detailed data extraction were carried out by Nedal Jaber, Ahmad Hodrob, Buthaina Nazzal, and Malakeh Z. Malak, focusing on methodological quality and relevance. Additional support in quality appraisal and data verification was provided by Nizar Said, Amer Asia, and Wafaa Qaysi. Discrepancies and conflicts during the screening or data extraction stages were resolved through consensus under the leadership of Mohammed Hayek. The initial search strategy yielded 2,791 records. After removing duplicates, 2,334 unique articles remained. Title screening excluded 1,548 records, and abstract screening led to the removal of 764 more. After full-text assessment, 13 randomized controlled trials (RCTs) met the inclusion criteria and were included in this systematic review. The complete study selection process is illustrated in the PRISMA flow diagram (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eData Extraction\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe data extraction process for this systematic review encompassed studies published between January 2013 and 5 December 2023, totaling 13 research articles. These studies uniformly focused on the integration of high-fidelity simulation within nursing education programs, with a specific emphasis on evaluating its effect on the clinical competencies of nursing students. Comprehensive details regarding trial attributes, participant demographics, interventions, control group descriptions, outcome measures related to clinical competency, and concluding remarks can be found in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, where each study is listed by (Author, year), country, participant characteristics, intervention group, control group, outcome measures pertaining to clinical competency, and key conclusions. In the following section, we provide a synthesized overview of the study characteristics and findings, aligning with the established PICO (Population, Intervention, Comparison, Outcome) framework for systematic reviews.\u003c/p\u003e\u003cp\u003e\u003cb\u003eQuality assessment and risk of bias\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe risk of bias in individual studies included in this systematic review was assessed using The Cochrane Collaboration's tool for assessing the risk of bias specific to randomized controlled trials (RCTs) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This tool comprehensively evaluates several key domains of potential bias (low risk, high risk, or unclear risk), ensuring the quality and validity of the RCTs in question. Each study was scrutinized for selection bias, with attention to random sequence generation and allocation concealment. Performance bias and detection bias were assessed by examining methods for blinding participants and outcome assessors. Attrition bias was evaluated by examining the handling of incomplete outcome data while reporting bias was examined by assessing whether all predefined outcomes were reported. Moreover, other sources of bias, such as baseline imbalances and funding sources, were considered in the risk of bias assessment. By rigorously applying The Cochrane Collaboration's tool, the systematic review aimed to provide a comprehensive and critical evaluation of each RCT's methodological quality and potential sources of bias. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e represents the Methodological Quality of Included Studies.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e Summary of Included Randomized Controlled Trial\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Author, year) / Country\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eParticipants Characteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eExperimental Group\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eControl Group\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOutcome Measures\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eConclusion\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Cengiz et al., 2023) / Turkey [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber: 112\u003c/p\u003e\u003cp\u003eLevel: first-year\u003c/p\u003e\u003cp\u003eIntervention: post-operative care\u003c/p\u003e\u003cp\u003eM/F: 31/81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber:57\u003c/p\u003e\u003cp\u003eAge:19.63 ± 1.19\u003c/p\u003e\u003cp\u003eIntervention: Scenario-based HFS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNumber:55\u003c/p\u003e\u003cp\u003eAge: 19.47 ± 1.08\u003c/p\u003e\u003cp\u003eIntervention: in-class learning sessions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eProblem-solving\u003c/p\u003e\u003cp\u003eSelf-efficacy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHFS outperforms in-class learning for problem-solving and self-efficacy.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Ozdemir \u0026amp; Kaya, 2023) / Turkey [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber: 80\u003c/p\u003e\u003cp\u003eLevel: first-year\u003c/p\u003e\u003cp\u003eIntervention: Foley catheterization\u003c/p\u003e\u003cp\u003eM/F: 7/73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber: 40\u003c/p\u003e\u003cp\u003eAge: 18.93 ± 1.05\u003c/p\u003e\u003cp\u003eIntervention: Scenario-based + HFS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNumber: 40\u003c/p\u003e\u003cp\u003eAge: 19.45 ± 1.92\u003c/p\u003e\u003cp\u003eIntervention: low fidelity simulation (LFS)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eKnowledge\u003c/p\u003e\u003cp\u003eperformance Satisfaction\u003c/p\u003e\u003cp\u003eSelf-confidence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHFS improved novice nursing students' knowledge, performance, satisfaction, and self-confidence more than LFS\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Hodrob et al., 2022) / Palestine [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber: 154\u003c/p\u003e\u003cp\u003eLevel: second-year\u003c/p\u003e\u003cp\u003eIntervention: airway management\u003c/p\u003e\u003cp\u003eM/F: 80/74\u003c/p\u003e\u003cp\u003eAge: 22.2 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber: 77\u003c/p\u003e\u003cp\u003eIntervention: HFS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNumber: 77\u003c/p\u003e\u003cp\u003eIntervention: lecture based\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eperformance\u003c/p\u003e\u003cp\u003esatisfaction\u003c/p\u003e\u003cp\u003eself-confidence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHFS proved effective in enhancing nursing students' airway management performance, boosting their satisfaction and self-confidence.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Guerrero et al., 2021) / Saudi Arabia [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber: 30\u003c/p\u003e\u003cp\u003eLevel: 1st to 4th\u003c/p\u003e\u003cp\u003eAge: 24–26 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber: 15\u003c/p\u003e\u003cp\u003eIntervention: HFS and hands-on training.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNumber: 15\u003c/p\u003e\u003cp\u003eIntervention: hands-on training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eperformance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHFS improves clinical performance.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Haddeland et al., 2021) / Norway [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber: 158\u003c/p\u003e\u003cp\u003eIntervention: blood loss after surgery\u003c/p\u003e\u003cp\u003eM/F: 19/139\u003c/p\u003e\u003cp\u003eAge: 21–22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber: 89\u003c/p\u003e\u003cp\u003eIntervention: HFS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNumber: 69\u003c/p\u003e\u003cp\u003eIntervention: lecture-based\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eKnowledge\u003c/p\u003e\u003cp\u003eself-confidence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHigh-fidelity simulation improves knowledge and self-confidence\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Doğru \u0026amp; Aydın, 2020) / Turkey [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber:72\u003c/p\u003e\u003cp\u003eLevel: first-year\u003c/p\u003e\u003cp\u003emean age: 19.95 ± 1.77\u003c/p\u003e\u003cp\u003eIntervention: cardiac auscultation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber: 36\u003c/p\u003e\u003cp\u003eIntervention: HFS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNumber: 36\u003c/p\u003e\u003cp\u003eIntervention: Static manikin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eKnowledge\u003c/p\u003e\u003cp\u003eperformance Anxiety\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUsing HFS outperformed traditional methods, improving students' knowledge and performance in cardiac auscultation while reducing anxiety.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Terzi et al., 2019) / Turkey [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber:59\u003c/p\u003e\u003cp\u003eLevel: first-year\u003c/p\u003e\u003cp\u003eIntervention: blood pressure measurement\u003c/p\u003e\u003cp\u003enursing students\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber: 32\u003c/p\u003e\u003cp\u003eIntervention: HFS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNumber: 27\u003c/p\u003e\u003cp\u003eIntervention: students practice on\u003c/p\u003e\u003cp\u003etheir peers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSelf-confidence\u003c/p\u003e\u003cp\u003eself-efficacy\u003c/p\u003e\u003cp\u003eAnxiety\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eThe HFS boosted students' self-confidence and self-efficacy but didn't impact their anxiety levels compared with practice on their peers\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Mutlu et al., 2019) / Turkey [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber: 71\u003c/p\u003e\u003cp\u003eLevel: 3rd and 4th -year\u003c/p\u003e\u003cp\u003eIntervention: heart and lung sounds\u003c/p\u003e\u003cp\u003eM/F: 0/71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber: 36\u003c/p\u003e\u003cp\u003eIntervention: HFS\u003c/p\u003e\u003cp\u003eMean age: 21.53 ± 0.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNumber: 35\u003c/p\u003e\u003cp\u003eIntervention: LFS\u003c/p\u003e\u003cp\u003eMean age: 21.74 ± 1.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eperformance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHFS more effective in heart and lung sounds performance.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Boostel et al., 2017) / Brazil [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber: 52\u003c/p\u003e\u003cp\u003eIntervention: cardiothoracic physical examination\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber: 27\u003c/p\u003e\u003cp\u003eMean age: 20.32 ± 1.79 Intervention: Theoretical /clinical class + HFS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNumber: 25\u003c/p\u003e\u003cp\u003eMean age: 21.11 ± 2.47\u003c/p\u003e\u003cp\u003eIntervention: Theoretical /clinical class\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCritical thinking\u003c/p\u003e\u003cp\u003eSelf-evaluation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSimulation influences perception of pressures, encourages critical thinking and Self-evaluation.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Labant \u0026amp; Palmer, 2017) / USA [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber: 26\u003c/p\u003e\u003cp\u003eLevel: junior-level\u003c/p\u003e\u003cp\u003eCourse: Maternal Neonate Clinical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber: 14\u003c/p\u003e\u003cp\u003eIntervention: lecture/video and hands-on training using a HFS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNumber: 12\u003c/p\u003e\u003cp\u003eIntervention: lecture/video\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eKnowledge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHFS group had lower discrepancy scores, closer to expert level and improve knoledge.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Baptista et al., 2016) / Portugal [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber: 85\u003c/p\u003e\u003cp\u003eLevel: 4th -year\u003c/p\u003e\u003cp\u003eIntervention: Critical condition\u003c/p\u003e\u003cp\u003eM/F: 6/79\u003c/p\u003e\u003cp\u003eMean age: 21.89 years (SD = 2.81 years).\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber: 49\u003c/p\u003e\u003cp\u003eIntervention: HFS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNumber: 36\u003c/p\u003e\u003cp\u003eIntervention: Medium-fidelity simulation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSatisfaction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHFS investment advantageous for student Satisfaction.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Aqel \u0026amp; Ahmad, 2014) / Jordan [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber: 90\u003c/p\u003e\u003cp\u003eM/F: 19/71\u003c/p\u003e\u003cp\u003eIntervention: CPR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber: 45\u003c/p\u003e\u003cp\u003eIntervention: HFS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNumber: 45\u003c/p\u003e\u003cp\u003eIntervention: LFS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eKnowledge\u003c/p\u003e\u003cp\u003eperformance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHFS excelled in knowledge and performance. Both experienced skill decline after three months.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(White et al., 2013) / USA [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber: 54\u003c/p\u003e\u003cp\u003eLevel: senior-level\u003c/p\u003e\u003cp\u003eIntervention: Distributive Shock\u003c/p\u003e\u003cp\u003eM/F: 7/47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber: 16\u003c/p\u003e\u003cp\u003eIntervention: HFS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNumber: 38\u003c/p\u003e\u003cp\u003eIntervention: lecture-based\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eKnowledge\u003c/p\u003e\u003cp\u003eSelf-confidence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eThe utilization of HFS did not lead to notable improvements in either Knowledge\u003c/p\u003e\u003cp\u003eor Self-confidence.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMethodological Quality of Included Studies\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAuthor (year)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRandom\u003c/p\u003e\u003cp\u003e(selection bias)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAllocation\u003c/p\u003e\u003cp\u003e(selection bias)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eperformance bias\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eDetection bias\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eattrition bias\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ereporting bias\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eOther Bias\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Cengiz et al., 2023) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnclear risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnclear risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHigh risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Ozdemir \u0026amp; Kaya, 2023) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003elow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ehigh risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ehigh risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehigh risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003elow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eHigh risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003ehigh risk\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Hodrob et al., 2022) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003elow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnclear risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnclear risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eUnclear risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003elow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003elow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003elow risk\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Guerrero et al., 2021) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003elow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003elow risk\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Haddeland et al., 2021) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003elow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003elow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003elow risk\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Doğru \u0026amp; Aydın, 2020) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ehigh risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ehigh risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehigh risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eunclear risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eHigh risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eUnclear risk\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Terzi et al., 2019) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003elow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ehigh risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ehigh risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehigh risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003elow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eHigh risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003ehigh risk\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Mutlu et al., 2019) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003elow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHigh risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eunclear risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehigh risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003elow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eHigh risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eUnclear risk\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Boostel et al., 2017) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHigh risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHigh risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHigh risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Labant \u0026amp; Palmer, 2017) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnclear risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnclear risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eUnclear risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003elow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003elow risk\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Baptista et al., 2016) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHigh risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHigh risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHigh risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Aqel \u0026amp; Ahmad, 2014) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnclear risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHigh risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHigh risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eLow risk\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(White et al., 2013) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003elow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHigh risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eunclear risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003elow risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eunclear risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eHigh risk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003ehigh risk\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e"},{"header":"Result","content":"\u003cp\u003e\u003cb\u003eParticipants and interventions\u003c/b\u003e:\u003c/p\u003e\u003cp\u003eThe research presented in this section encompasses thirteen distinct studies, collectively involving 1,320 participants, and explores various facets of healthcare education across different regions and interventions. These studies shed light on the diversity of approaches and methodologies employed in healthcare education research, reflecting the global nature of this field. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the methodological quality assessment of 13 included randomized controlled trials, highlighting varying levels of bias across different domains. Random sequence generation (selection bias) was rated as low risk in all studies, suggesting appropriate randomization methods. However, allocation concealment showed more variability, with several studies such as Ozdemir \u0026amp; Kaya (2023) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], Doğru \u0026amp; Aydın (2020) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], and others rated as high risk, indicating potential bias in group assignment. Performance and detection bias were frequently rated as high or unclear, especially in studies involving educational interventions where blinding was challenging. Attrition bias was mostly low across studies, suggesting acceptable handling of dropouts. While reporting bias was generally low, a few studies like Ozdemir \u0026amp; Kaya (2023) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] and Terzi et al. (2019) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] had high risk, indicating selective outcome reporting. Other bias was often rated as low, though some studies presented unclear or high risk. Overall, while most studies demonstrated adequate randomization, concerns remain about blinding and allocation concealment, potentially impacting internal validity.\u003c/p\u003e\u003cp\u003eIn our examination of the control groups within these studies, we observe a wide range of interventions and participant characteristics. These variations underscore the need for flexibility in healthcare education research to cater to the specific needs and contexts of different regions and institutions. For instance, Cengiz et al. and Ozdemir \u0026amp; Kaya in Turkey employed traditional in-class learning and \"LFS,\" respectively, as control interventions, emphasizing the importance of comparing innovative educational methods with established ones [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Hodrob et al. in Palestine and Haddeland et al. in Norway utilized lecture-based teaching in their control groups, emphasizing the global prevalence of this traditional approach [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In contrast, Doğru \u0026amp; Aydın in Turkey, Terzi et al., and Mutlu et al. exclusively employed static manikins, reflecting the range of simulation tools available for healthcare education [\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e–\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Boostel et al. in Brazil and Labant \u0026amp; Palmer in the USA integrated theoretical and clinical class-based education in their control groups, highlighting the importance of theoretical foundations in healthcare education [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Baptista et al. in Portugal introduced medium-fidelity simulation for their control group, showcasing the diverse spectrum of simulation technologies [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Finally, Aqel \u0026amp; Ahmad in Jordan and White et al. in the USA used \"LFS\" and lecture-based instruction, respectively, as control interventions, indicating that traditional methods persist alongside innovative approaches [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTurning our attention to the experimental groups, we find an equally diverse set of interventions and participant characteristics. The variety of educational approaches reflects the dynamic nature of healthcare education research. For example, Cengiz et al. and Ozdemir \u0026amp; Kaya in Turkey incorporated scenario-based High-Fidelity Simulation (HFS) in their experimental groups, underscoring the growing importance of immersive simulation experiences [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Hodrob et al. in Palestine and Haddeland et al. in Norway exclusively employed HFS, emphasizing its effectiveness in teaching critical healthcare skills [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Guerrero et al. (2021) in Saudi Arabia combined HFS with hands-on training, showcasing the potential benefits of multifaceted approaches. Similarly, Doğru \u0026amp; Aydın, Terzi et al., and Mutlu et al. in Turkey embraced HFS as the primary mode of intervention, aligning with the trend toward high-fidelity simulations [\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e–\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Boostel et al. in Brazil integrated theoretical/clinical classes with HFS, reflecting a comprehensive approach to healthcare education [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Labant \u0026amp; Palmer in the USA combined lecture, video, and hands-on training, demonstrating the importance of multimodal education [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Baptista et al. in Portugal focused exclusively on HFS for their experimental group, indicating the significance of this simulation method [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Finally, Aqel \u0026amp; Ahmad in Jordan and White et al. in the USA employed HFS as the primary mode of intervention in their experimental groups, further highlighting its prominence [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eOutcome measures\u003c/b\u003e:\u003c/p\u003e\u003cp\u003e\u003cb\u003eKnowledge\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSix articles revealed that the high-fidelity simulation enhanced the knowledge among undergraduate nursing students. A recently conducted study in Turkey by Ozdemir and Kaya, found the knowledge among the students who had the opportunity of training through HFS and Scenario-based learning on foly catheterization was higher than the students of Low-Fidelity Simulation [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Another conducted study by Doğru and Aydın, In Turkey, found that the HFS in comparison to traditional teaching methods improved significantly the level of knowledge in cardiac auscultation [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Haddeland et al., conducted a study among Norway undergraduate nursing students and found that HFS improved knowledge about blood loss after surgery in comparison to the control group who received lecture-based education [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Labant and Palmer, found the effect of HFS in addition to the hands-on training on knowledge among undergraduate students who underwent a Maternal and Neonatal clinical course is better than the students who received training via lectures and videos [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. These are similar to another two studies in which the level of knowledge where targeted and improved, the HFS training where about CPR versus LFS for the first study and the other was about Distributive Shock for the group of HFS and lecture-based education [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003ePerformance\u003c/b\u003e\u003c/p\u003e\u003cp\u003esix studies from various locations demonstrated a significant improvement in clinical performance skills through high-fidelity simulation. Ozdemir and Kaya (2023)in Turkey compared high-fidelity simulation for Foley catheterization skills with routine teaching methods, concluding that high-fidelity simulation significantly enhanced clinical performance skills in this context. Guerrero et al. in Saudi Arabia investigated the impact of simultaneous high-fidelity simulation and hands-on clinical training on clinical performance skills among 120 nursing interns, with results indicating an improvement [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Labant and Palmer in the USA studied 26 junior-level nursing students and found that high-fidelity simulation manikin training effectively improved clinical performance skills, bringing participants closer to expert-level performance [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Mutlu et al. in Turkey compared high-fidelity and low-fidelity simulators for heart and lung sound recognition among 71 third-year female nursing students, concluding that high-fidelity simulation was more effective in this aspect [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Aqel and Ahmad compared the HFS effects on the performance of undergraduate students versus Low Fidelity Simulation on Cardiopulmonary Resuscitation and found that the HFS is better than the LFS group in conducting CPR [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Furthermore, Doğru and Aydın, in Turkey examined the effectiveness of simulation for administering intra-muscular injections among 72 first-year nursing students, concluding that simulation was effective in enhancing clinical performance skills [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Hodrob et al. found that HFS for teaching students airway management is better than the lecture-based methodology among undergraduate nursing students [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eSelf-Confidence.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSelf-confidence in nursing education emerges as a complex and nuanced theme when examining the findings of the five pertinent articles. Ozdemir \u0026amp; Kaya's study conducted in Turkey underscored that High-Fidelity Simulation (HFS) contributed significantly to enhancing self-confidence among novice nursing students [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Similarly, Hodrob et al.'s research in Palestine observed a notable boost in self-confidence following HFS interventions focused on airway management performance [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Terzi et al. and Haddeland et al. yielded results aligned with these findings, showing an improvement in students' self-confidence [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Conversely, White et al. in the USA did not report substantial improvements in self-confidence through HFS [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eSatisfaction\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSatisfaction with the educational approach was explored in 3 studies. Ozdemir \u0026amp; Kaya (2023) and Hodrob et al. found that HFS improved student satisfaction [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Baptista et al. in Portugal also emphasized the advantageous nature of HFS investment for student satisfaction [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eSelf-Efficacy\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSelf-efficacy was another critical competency assessed in these studies. Two studies out of 13 studies examined Self-Efficacy among the groups, Cengiz et al. in Turkey found that high-fidelity simulation improved self-efficacy among first-year nursing students [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Another study found that self-efficacy improved among the HFS more than the group who practiced on their peers in terms of blood pressure measurement [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eAnxiety\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTwo studies addressed the issue of anxiety. Doğru \u0026amp; Aydın reported that HFS reduced anxiety levels, suggesting that it can create a more comfortable learning environment [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, Terzi et al. did not find significant differences in anxiety levels compared to peer practice, indicating that the impact of HFS on anxiety may vary [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eProblem-Solving\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOnly one study out of the 13 studies included in this systematic review found that the HFS had a higher influence in promoting problem-solving skills among undergraduate nursing students compared to the in-class learning sessions. Cengiz et al. conducted a study among the first year of undergraduate nursing students to examine the problem-solving skills related to post-operative care and found the HFS group had better skills compared to the in-class learning sessions group [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eSelf-Evaluation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eExamining the findings of Boostel et al.'s study conducted in Brazil [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], self-evaluation emerges as a crucial dimension of nursing education impacted by HFS. The research underscores that HFS encourages nursing students to engage in rigorous self-assessment and reflection on their performance and decision-making processes within simulated clinical scenarios. By actively participating in the simulation experience and evaluating their actions, students can identify areas for improvement and refine their clinical competencies. Boostel et al.'s findings emphasize the role of HFS in fostering a culture of self-awareness and self-improvement among nursing students, ultimately contributing to their growth as reflective and accountable healthcare professionals [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. This highlights the significance of incorporating HFS as an effective tool for enhancing self-evaluation skills within nursing education programs\u003c/p\u003e\u003cp\u003e\u003cb\u003eCritical thinking\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDrawing insights from Guerrero et al.'s research in Saudi Arabia, critical thinking emerges as a pivotal aspect of nursing education [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The study underscores the significant role that HFS plays in influencing critical thinking skills among nursing students. This research highlights that HFS interventions contribute to fostering the ability of students to analyze complex clinical scenarios, question assumptions, and make informed decisions. As demonstrated in the study, HFS provides a conducive environment for students to practice critical thinking within the context of real-life clinical situations, enhancing their capacity to address challenges in healthcare effectively. Consequently, this emphasizes the vital importance of integrating HFS into nursing curricula to cultivate the critical thinking skills essential for future nursing professionals.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe study showed that the high-fidelity simulation positively impacted knowledge. A recent study showed that clinical competency improved in performing the Foley catheterization, in addition to improvement their knowledge [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. This is similar to the result of other published studies [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. On the other hand, multiple studies showed the positive influence of HFS on undergraduate nursing student's performance [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This reveals the potential of high-fidelity simulation as a good tool in education and training, which leads to nurses graduating with better theoretical and clinical skills, and this can be interpreted in more patient safety and improved nursing confidence. The study revealed another finding, including a positive enhancement of student\u0026rsquo;s critical thinking skills, problem-solving skills, and decision-making skills. According to Cengiz et al., the high-fidelity simulation positively impacted the students\u0026rsquo; skills in problem-solving [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Critical thinking also impacted positively [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This implies that the immersive and realistic quality of high-fidelity simulation scenarios can help students gain more management and leadership skills. The studies revealed another positive outcome for high-fidelity simulation among undergraduate nurses, such as improved student self-confidence and self-efficacy. Terzi et al. found that the self-confidence among the students enhanced related to high fidelity simulation [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. These results are similar to the results of other studies [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. These results in contrast to one study result [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Self-efficacy showed improvement among the students of high-fidelity simulation as reported by Cengiz et al [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e The systematic review results showed another positive outcome for the high-fidelity simulation. Hodrob et al. and Ozdemir \u0026amp; Kaya [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], reported that satisfaction was improved among the students due to high-fidelity simulation. While the level of anxiety was impacted positively due to HFS Doğru \u0026amp; Aydın, and Terzi et al. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] Also, the self-evaluation among the students was encouraged and enhanced [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. This implies that the immersive and realistic quality of high-fidelity simulation scenarios can help students confidently approach clinical issues, which is essential in the healthcare industry. These findings show the overall benefits of high-fidelity simulation in nursing education. It not only improves clinical capabilities, but it also improves students' general contentment, mental health, and critical thinking ability. This all-encompassing approach to nursing education can result in balanced, confident, and competent nursing practitioners who are better prepared to fulfill the needs of the healthcare industry.\u003c/p\u003e\u003cp\u003eHigh-fidelity simulation is a valuable tool for enhancing the clinical competencies of undergraduate nursing students. However, its effectiveness is influenced by various factors, such as the simulation scenario, the debriefing process, and the instructor's role. Therefore, we suggest that nursing educators use high-fidelity simulation as a complementary method to traditional clinical education, rather than a replacement. We also recommend that nursing educators follow evidence-based guidelines and best practices for designing, implementing, and evaluating high-fidelity simulation. Furthermore, we encourage nursing educators to collaborate with other disciplines and institutions to share their experiences and resources for high-fidelity simulation. In addition to these recommendations. Future research in this area should aim to address the identified limitations and provide a more comprehensive understanding of the role of high-fidelity simulation in nursing education. Additionally, ongoing evaluation of the evolving technology and educational practices is crucial to ensure the continued relevance and effectiveness of high-fidelity simulation in preparing nursing students for clinical practice.\u003c/p\u003e\u003cp\u003eThis study was limited to undergraduate nursing students in English-language studies published between 2013 and 2023. Thus, the findings may not be generalizable to other populations or periods.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, the comprehensive review of thirteen diverse studies in healthcare education reveals a multifaceted landscape of interventions, outcomes, and participant characteristics. These studies collectively involve 1,320 participants and span various regions, shedding light on the global nature of healthcare education research. In examining the control and experimental groups, it becomes evident that the interventions employed vary widely, reflecting the flexibility required to cater to the unique needs and contexts of different regions and institutions. Traditional methods, lecture-based teaching, hands-on training, and a range of simulation technologies all find a place within the spectrum of interventions. Notably, High-Fidelity Simulation (HFS) emerges as a prominent educational tool, positively impacting knowledge acquisition, clinical performance, self-confidence, and self-evaluation. While HFS consistently demonstrates its effectiveness, other dimensions such as self-efficacy, satisfaction, and anxiety exhibit varying results across studies. Critical thinking and problem-solving skills also gain importance as outcomes are influenced by HFS, as demonstrated in the relevant research. These findings underscore the dynamic and adaptive nature of healthcare education, emphasizing the need for educators and institutions to continually evaluate and integrate innovative approaches like HFS to ensure the best possible education for future healthcare professionals.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis systematic review did not involve human subjects directly; therefore, ethical approval was not sought. The review exclusively focused on the analysis of previously published research articles and did not require primary data collection from individuals or the involvement of ethical review boards.\u003c/p\u003e\n\u003ch2\u003eClinical trial registration\u003c/h2\u003e\n\u003cp\u003eClinical trial number: not applicable.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eThe initial electronic search across databases was conducted by Ibrahim Ghoul, who also removed duplicate records using EndNote. Title screening was performed by Abdullah Abdullah and Shurouq Qadous, followed by abstract screening by Mahmoud Hodrob and Fateh Awwad. Full-text assessment for eligibility and detailed data extraction were carried out by Nedal Jaber, Ahmad Hodrob, Buthaina Nazzal, and Malakeh Z. Malak, focusing on methodological quality and relevance. Additional support in quality appraisal and data verification was provided by Nizar Said, Amer Asia, and Wafaa Qaysi. Discrepancies and conflicts during the screening or data extraction stages were resolved through consensus under the leadership of Mohammed Hayek.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eThe authors would like to thank An-Najah National University (www.najah.edu) for the technical support provided to publish the present manuscript\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon a reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLei Y, Zhu L, Sa Y, Cui X-S. Effects of high-fidelity simulation teaching on nursing students' knowledge, professional skills and clinical ability: A meta-analysis and systematic review. Nurse Educ Pract. 2022;60:103306.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHanshaw S, Dickerson S. High fidelity simulation evaluation studies in nursing education: A review of the literature. Nurse Educ Pract. 2020;46:102818.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlshehri F, Jones S, Harrison D. The effectiveness of high-fidelity simulation on undergraduate nursing students' clinical reasoning-related skills: A systematic review. Nurse Educ Today. 2022;121:105679.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFung J, Chan SL, Chan CK, Lam CF, Chau YS, Lam WH, Cheng CCW, Lai MH. Enhancing nursing students' clinical competency using a multi-patient simulation learning model: A randomized controlled study. Nurse Educ Today. 2024;140:106292.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAyed A, Malak M, Alamer R, Batran A, Salameh B, Fashafsheh I. Effect of high fidelity simulation on clinical decision-making among nursing students. Interact Learn Environ. 2021;31:2185\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAyed A, Khalaf I, Fashafsheh I, Saleh A, Bawadi H, Abuidhail J, Thultheen I, Joudallah H. Effect of High-Fidelity Simulation on Clinical Judgment Among Nursing Students. Inquiry: J Med Care Organ Provis Financing 2022, 59.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChabrera C, Curell L, Rodr\u0026iacute;guez-Higueras E. Effectiveness of high versus mixed-level fidelity simulation on undergraduate nursing students: A randomised controlled trial. Nurse Educ Pract. 2024;82:104206.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBlum C, Borglund S, Parcells D. High-Fidelity Nursing Simulation: Impact on Student Self-Confidence and Clinical Competence. Int J Nurs Educ Scholarsh 2010, 7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eO'Rourke L, Morrison M, Grimsley A, Cotter V. High-fidelity simulation and nurse clinical competence-An integrative review. J Clin Nurs 2021.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e王 X晓W, 杨 Y, 胡 S莎H. Teaching nursing students: As an umbrella review of the effectiveness of using high-fidelity simulation. Nurse Educ Pract. 2024;77:103969.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMoher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M, Shekelle P, Stewart LA. Group P-P: Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst reviews. 2015;4:1\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHiggins JP, Altman DG, G\u0026oslash;tzsche PC, J\u0026uuml;ni P, Moher D, Oxman AD, Savović J, Schulz KF, Weeks L, Sterne JA. The Cochrane Collaboration\u0026rsquo;s tool for assessing risk of bias in randomised trials. \u003cem\u003ebmj\u003c/em\u003e 2011, 343.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCengiz Z, G\u0026uuml;rdap Z, Oltuluoğlu H, Aslan H, Aktura S\u0026Ccedil;. Developing nursing students' self-efficacy and problem solving skills via high-fidelity simulation. Teach Learn Nurs. 2023;18(4):e167\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOzdemir NG, Kaya H. The effectiveness of high-fidelity simulation methods to gain Foley catheterization knowledge, skills, satisfaction and self-confidence among novice nursing students: A randomized controlled trial. Nurse Educ Today. 2023;130:105952.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHodrob AMS, Malak MZ, Ayed A. Effect of high-fidelity simulation airway management training program on nursing students\u0026rsquo; performance, satisfaction, and self-confidence in Palestine. Interact Learn Environ. 2024;32(1):325\u0026ndash;39.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuerrero JG, Hafiz AH, Eltohamy NAE, Gomma N, Al Jarrah I. Repeated exposure to high-fidelity simulation and nursing interns\u0026rsquo; clinical performance: impact on practice readiness. Clin Simul Nurs. 2021;60:18\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHaddeland K, Sletteb\u0026oslash; \u0026Aring;, Svensson E, Tosterud RB, Wangensteen S, Fossum M. The effects of using high-fidelity simulation in undergraduate nursing education: A multicenter randomized controlled trial with a process evaluation. Int J Educational Res. 2021;109:101813.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDoğru BV, Aydın LZ. The effects of training with simulation on knowledge, skill and anxiety levels of the nursing students in terms of cardiac auscultation: A randomized controlled study. Nurse Educ Today. 2020;84:104216.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTerzi B, Topbaş E, Bing\u0026ouml;l G, Aydoğdu SGM. Comparison of the effects of two different teaching methods in blood pressure measurement training: a randomized controlled study. Blood Press Monit. 2019;24(6):294\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMutlu B, Yılmaz OE, Dur S. The effect of high-and low-fidelity simulators in learning heart and lung sounds by undergraduate nurses: a randomized controlled trial. Contemp Nurse. 2019;55(4\u0026ndash;5):351\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBoostel R, Felix JVC, Bortolato-Major C, Pedrolo E, Vayego SA. Mantovani MdF: Tensi\u0026oacute;n del estudiante de enfermer\u0026iacute;a en la simulaci\u0026oacute;n cl\u0026iacute;nica: ensayo cl\u0026iacute;nico aleatorizado. Revista Brasileira de Enfermagem. 2018;71:967\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLabant AL, Palmer EA. Teaching neonatal abstinence syndrome using simulation. Clin Simul Nurs. 2017;13(6):254\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBaptista RC, Paiva LA, Goncalves RF, Oliveira LM, Pereira MFC, Martins JC. Satisfaction and gains perceived by nursing students with medium and high-fidelity simulation: A randomized controlled trial. Nurse Educ Today. 2016;46:127\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAqel AA, Ahmad MM. High-fidelity simulation effects on CPR knowledge, skills, acquisition, and retention in nursing students. Worldviews Evidence‐Based Nurs. 2014;11(6):394\u0026ndash;400.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWhite A, Brannan J, Long J, Kruszka K. Comparison of instructional methods: Cognitive skills and confidence levels. Clin Simul Nurs. 2013;9(10):e417\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"High-Fidelity Simulation, Undergraduate Nursing Students","lastPublishedDoi":"10.21203/rs.3.rs-7234638/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7234638/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e\u003cp\u003eHigh-fidelity simulation (HFS) has gained prominence in nursing education as a method to enhance clinical competencies in undergraduate nursing students. This systematic review examines the impact of HFS on various aspects of nursing students' clinical competencies.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e\u003cp\u003e Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we conducted a comprehensive search for randomized controlled trials (RCTs) published in English between 2013 and 2023. Inclusion and exclusion criteria were applied, leading to the selection of 13 relevant studies. Quality assessment and risk of bias analysis were performed using The Cochrane Collaboration's tool for RCTs.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e\u003cp\u003e The systematic review synthesized findings from the selected studies, revealing the positive impact of HFS on nursing students' clinical competencies. These competencies encompassed knowledge acquisition, clinical performance, self-confidence, self-evaluation, critical thinking, problem-solving skills, and anxiety reduction. While there was variability in outcomes such as self-efficacy and satisfaction, HFS consistently demonstrated its effectiveness in enhancing nursing education.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn conclusion, HFS emerges as a valuable tool for improving the clinical competencies of undergraduate nursing students. This systematic review highlights the multifaceted benefits of HFS in nursing education, encouraging its integration alongside traditional clinical methods. Recommendations include following evidence-based guidelines and fostering collaboration among educators and institutions to further enhance nursing education through HFS.\u003c/p\u003e","manuscriptTitle":"The effect of high-fidelity simulation on clinical competencies in undergraduate nursing students: a systematic review of randomized controlled trials","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-25 10:14:09","doi":"10.21203/rs.3.rs-7234638/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d9602da9-9b57-4cd5-9aa2-e9fac9dc54af","owner":[],"postedDate":"August 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-09T05:38:53+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-25 10:14:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7234638","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7234638","identity":"rs-7234638","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}